Inter- and intra-individual variability in alpha peak frequency

Abstract

Converging electrophysiological evidence suggests that the alpha rhythm plays an important and active role in cognitive processing. Here, we systematically studied variability in posterior alpha peak frequency both between and within subjects. We recorded brain activity using MEG in 51 healthy human subjects under three experimental conditions — rest, passive visual stimulation and an N-back working memory paradigm, using source reconstruction methods to separate alpha activity from parietal and occipital sources. We asked how alpha peak frequency differed within subjects across cognitive conditions and regions of interest, and looked at the distribution of alpha peak frequency between subjects. In both regions we observed an increase of alpha peak frequency from resting state and passive visual stimulation conditions to the N-back paradigm, with a significantly higher alpha peak frequency in the 2-back compared to the 0-back condition. There was a trend for a greater increase in alpha peak frequency during the N-back task in the occipital vs. parietal cortex. The average alpha peak frequency across all subjects, conditions, and regions of interest was 10.3 Hz with a within-subject SD of 0.9 Hz and a between-subject SD of 2.8 Hz. We also measured beta peak frequencies, and except in the parietal cortex during rest, found no indication of a strictly harmonic relationship with alpha peak frequencies. We conclude that alpha peak frequency in posterior regions increases with increasing cognitive demands, and that the alpha rhythm operates across a wider frequency range than the 8–12 Hz band many studies tend to include in their analysis. Thus, using a fixed and limited alpha frequency band might bias results against certain subjects and conditions.

Theta–gamma cross-frequency coupling relates to the level of human intelligence

“…In addition, the results of the present study lend support to the P-FIT model of intelligence, which states that a frontal-parietal network underpins the neurobiology of intelligence (Jung & Haier, 2007). It would be interesting to investigate whether restingstate theta-gamma coupling is stable over time, which would imply "trait-like" properties similar to individual alpha frequency (Haegens, Cousijn, Wallis, Harrison, & Nobre, 2014). If that were the case, inter-subject variability in theta-gamma coupling could, in principle, explain differences in overall cognitive performance.…”

Exploring the relationship of phase and peak-frequency EEG alpha-band and beta-band activity to temporal judgments of stimulus duration

“…In line with previous findings (Cravo et al, 2015;Mathewson et al, 2009;Milton & Pleydell-Pearce, 2016;Varela et al, 1981), we predicted an effect in the alpha range (7-14 Hz, see Haegens, Cousijn, Wallis, Harrison, & Nobre, 2014 for justification of this definition of the alpha-band frequency range), so analysis focused on a cluster of occipital electrodes (O1, O2, POZ, OZ). An occipital cluster was chosen due to its relevance to the visual nature of the task, and because occipital electrodes have been previously demonstrated to be associated with phase effects on temporal judgments (Milton & Pleydell-Pearce, 2016;Varela et al, 1981), and previous effects of peak alphaband frequency on two-flash discrimination have been reported at occipital electrodes (Coffin & Ganz, 1977;.…”

“…IBF was calculated using the procedure outlined in Haegens et al (2014). Using least-squares linear regression, the 1/f component of the log-transformed spectrum (15-25 Hz) was modelled and subtracted from the spectrum to allow more reliable detection of the peak (again using findpeaks.m) frequency in the beta range (15-25 Hz).…”

Frequency-specific electrophysiologic correlates of resting state fMRI networks

“…2 and S6). The sharpness of these features and the possibility of inter-subject frequency variability (e.g., of the alpha band, see (Haegens et al, 2014)) underscores the importance of either well resolved spectral analyses or perhaps individually tuned frequency bins.…”